While Faster and Cheaper Sprint Ahead, Better Prepares for the Real Race.

I’m certain that you too have noticed that the tone on LinkedIn about AI impact is shifting. What felt like revolution six months ago increasingly feels like incremental improvement. The breathless claims about transformation are giving way to quiet frustration about implementation reality. Perhaps you yourself felt this earlier than others.

This isn't random disillusionment. It's Gartner's hype cycle playing out faster than any previous technology adoption. We're approaching the peak of inflated expectations at remarkable speed. And the trough of disillusionment isn't theoretical, it’s arriving in Q1 2026.

Understanding why this is inevitable requires understanding what makes industrial revolutions different from normal innovation.

Every project manager knows the iron triangle: faster, cheaper, better. Pick two.

You can have it fast and cheap, but quality suffers. You can have it fast and good, but it costs more. You can have it cheap and good, but it takes time. This tradeoff is fundamental to how resources, capability, and quality interact.

Normal innovation operates within this constraint. You optimise one or two dimensions while accepting compromise on the third. Better software that costs more. Cheaper manufacturing that takes longer to scale. Faster delivery that sacrifices customisation.

Industrial revolutions are different. They break the iron triangle entirely and let humanity achieve all three dimensions simultaneously. The tradeoff dissolves. This is why they're revolutions rather than innovations.

AI has this revolutionary potential. But here's what history reveals about every previous industrial revolution: faster and cheaper arrive before better.

The timeline mismatch creates the hype cycle.

Steam engines initially just replaced horses, faster and cheaper horsepower. Years passed before manufacturers redesigned factories around centralised power, unlocking the "better" that defined the revolution. Early electricity replaced gas lamps for faster and cheaper light. Years passed before electrical appliances transformed domestic life.

The internet initially just accelerated existing communication where faster and cheaper email versus postal mail. The "better" that rebuilt commerce, media, and social interaction took years to emerge.

With AI, we're in the "faster and cheaper" phase. AI accelerates existing processes. It reduces costs of current workflows. The tools getting adopted now are those that fit this pattern.

The “better”, or the fundamental transformation of what's possible, the strategic capabilities that didn't exist before, takes longer to develop. It requires deeper technology. It demands new methodologies. It resists quick wins and quarterly narratives.

This timeline mismatch explains the looming disillusionment. We're seeing faster and cheaper AI everywhere and assuming better has also arrived. When better doesn't materialise at the same speed, the trough hits.

Here's why this is inevitable, what's causing it, and what separates organisations that survive the trough from those that don't.

The market is flooded with "faster and cheaper" AI tools because faster and cheaper AI is itself faster and cheaper to build and launch.

The MVP of any AI tool will be the lazy version by definition. Take existing processes, add AI acceleration, ship quickly, capture market share. Most of them are just LLM-wrappers anyway. It's the obvious playbook. Create AI survey analysis that codes sentiment instantly. Deploy programmatic optimisation that adjusts creative in real-time.

And in every case, boards and investors and advisors are encouraging that quick launch. Get to market. Establish share of mind. Claim first-mover advantage. Show traction for the next funding round. The incentive structure rewards speed over substance.

This explains the AI pollution across marketing services. Not because people are cynical or lazy, but because smart teams are making rational decisions given their constraints. They have 18 months of runway. Their board expects revenue growth. Their competitors just launched. The path of least resistance is building what can ship quickly, not what creates lasting value.

Because of this, we’re adopting AI at the tactical execution end of the marketing value chain, with limited adoption at the insights, strategy, and innovation end.

I understand why lazy AI dominates because I feel that exact pressure building simbioniq.

We watched competitors launch synthetic consumer tools weekly while we spent six months developing Trait-Gated Query Logic™. Every instinct screamed to ship faster. Build the obvious thing: AI-powered focus groups that run in hours. Get traction. Show growth. Raise capital. Iterate later.

The advice from every experienced operator was consistent: build fast, launch faster, optimise later. Don't overthink it. The market rewards first movers. Your version one doesn't need to be transformative, it needs to exist.

We had one advantage that bought us discipline: the founders were the only investors through to seed stage. We could afford to wait for patent-pending technology before sharing externally. We could choose "better" over "fast" without immediate pressure to show traction for the next funding round.

Most teams don't have that luxury. And this isn't judgment, it’s empathy for the impossible position most AI builders face. They're making rational decisions given real constraints. Limited runway. Board pressure. Competitive dynamics. The path of least resistance leads directly to lazy AI.

So they build what boards will fund and timelines will allow. They optimise familiar processes rather than creating new capabilities. They deliver efficiency improvements that fit quarterly narratives rather than strategic transformations that require years to prove.

The result is an industry launching tools that promise transformation but deliver optimisation. And when those tools disappoint. When the 15% efficiency gains don't justify the revolution narrative, the entire category gets marked down in credibility.

At Simbioniq, we chose "better than people" as our standard, not "better than AI personas." Our Simbions don't just simulate faster focus groups. They represent the underrepresented 80% who determine success but never speak up in traditional research:

They maintain perfect memory across months of conversation so you can reference a concept discussed weeks ago and explore it deeper.

They explain emotional reactions better than people who feel strongly but struggle to articulate why. They don't just match human capability in specific, valuable ways, they exceed it.

This took six months to build with one client while competitors launched in weeks. But when lazy AI tools fail to deliver transformation, and when AI pricing rises to reflect real infrastructure costs, we'll have something that creates defensible strategic capability.

Good clients recognise the difference between lazy optimisation and transformative capability. These faster and cheaper options will fall away. We're building something to last.

When the lazy AI tools fail to deliver strategic transformation, because they were never designed to, because they're only optimising for two dimensions, the category suffers reputational damage. That 15% efficiency improvement doesn't justify the revolution narrative leadership sold to boards.

Executives expected all three dimensions simultaneously. They were promised revolution. They got optimisation.

The faster and cheaper advantage evaporates when pricing normalises. Only the "better" capabilities (those creating new strategic possibilities) survive the price correction.

The companies that survive the trough aren't those that shipped first or cheapest. They're those that built capabilities completing all three dimensions: faster AND cheaper AND better.

These teams understood the timeline mismatch. They didn't mistake early faster/cheaper tools for the complete revolution. They invested in the harder work of building genuine strategic capabilities while competitors chased efficiency metrics.

When the trough passes, they'll own the recovery. Because they built for the complete revolution, not just the first phase.

The next six to nine months will separate AI investments into two categories:

These are efficiency plays built on artificially low AI pricing. When costs rise to reflect actual infrastructure investment (and they must) the value proposition evaporates.

Teams that invested heavily in tactical optimisation without strategic capability will discover they've built nothing defensible. Their AI spend delivered temporary efficiency, not sustainable advantage.

The warning signs:

These are capabilities that enable something previously impossible, not just acceleration of existing processes. Strategic planning augmentation. Consumer understanding transformation. Innovation potential that didn't exist before.

These remain valuable when AI pricing rises because they create new strategic capability rather than cheaper existing processes. The teams building for this category are making harder choices now (longer development cycles, messier metrics, more difficult board presentations) but they're building things that last.

The distinguishing characteristics:

The trough is coming. The organisations that survive it are those honest about which AI investments create lasting value.

This is another industrial revolution. But like every revolution before it, the timeline creates disillusionment.

Steam power disappointed before it transformed manufacturing as initial adopters just got faster, cheaper horsepower while waiting decades for the factory redesign that unlocked "better." Electricity underdelivered before it restructured society as early adopters just replaced gas lamps while waiting years for the appliances that transformed domestic life. The internet bubble burst before it rebuilt commerce when investors funded faster, cheaper communication while the "better" took years to emerge.

The pattern is consistent: faster and cheaper arrive first. Better takes longer. The gap between them creates the trough.

The AI trough will feel like failure. Lazy AI tools optimising for faster and cheaper will collapse first, taking credibility with them. Budget pressure will mount. Boards will question the entire category. The vendors who built for speed and cost rather than capability will pivot, fold, or get acquired for pennies.

But amongst all the hyperventilating claims and launches and updates, some teams are building the "better" that completes the revolution. They're not just optimising speed and cost within existing processes. They're creating capabilities that didn't exist before. They're accepting longer development cycles because they understand the timeline mismatch.

They're choosing to build things that last.

What are you building?

Brandflow is written by Justin Billingsley, who has spent his career on all three sides of the industry's table: senior client, global agency leader, technology founder. First published 29 October 2025 in the Brandflow newsletter on LinkedIn.